Abstract:
PURPOSE:The objective of medical content-based image retrieval (CBIR) is to assist clinicians in decision making by retrieving the most similar cases to a given query image from a large database. Herein, a new method for content-based image retrieval of cone beam CT (CBCT) scans is presented. METHODS:The introduced framework consists of two main phases: training database construction and querying. The goal of the training phase is database construction, which consists of three main steps. First, automatic segmentation of lesions using 3D symmetry analysis is performed. Embedding the prior shape knowledge of the 3D symmetry characteristics of the healthy human head structure increases the accuracy of automatic segmentation. Then, spatial pyramid matching is used for feature extraction, and the relative importance of each feature is learned using classifiers. RESULTS:The method was applied to a dataset of 1145 volumetric CBCT images with four classes of maxillofacial lesions. A symmetry-based analysis model for automatic lesion segmentation was evaluated using similarity measures. Mean Dice coefficients of 0.89, 0.85, 0.92, and 0.87 were achieved for maxillary sinus perforation, radiolucent lesion, unerupted tooth, and root fracture classes, respectively. Moreover, the execution time of automatic segmentation was reduced to 3 min per case. The performance of the proposed search engine was evaluated using mean average precision and normalized discounted cumulative gain. A mean average retrieval accuracy and normalized discounted cumulative gain of 0.90 and 0.92, respectively, were achieved. CONCLUSION:Quantitative results show that the proposed approach is more effective than previous methods in the literature, and it can facilitate the introduction of CBIR in clinical CBCT applications.
journal_name
Int J Comput Assist Radiol Surgauthors
Abdolali F,Zoroofi RA,Otake Y,Sato Ydoi
10.1007/s11548-019-01946-wsubject
Has Abstractpub_date
2019-05-01 00:00:00pages
785-796issue
5eissn
1861-6410issn
1861-6429pii
10.1007/s11548-019-01946-wjournal_volume
14pub_type
杂志文章abstract:PURPOSE:A retrospective evaluation of the ability of computer-aided detection (CAD) ability to identify breast carcinoma in standard mammographic projections. MATERIALS AND METHODS:Forty-five biopsy proven lesions in 44 patients imaged digitally with CAD applied at examination were reviewed. Forty-four screening BIRAD...
journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
doi:10.1007/s11548-009-0300-7
更新日期:2009-06-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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更新日期:2020-10-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章,评审
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journal_title:International journal of computer assisted radiology and surgery
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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journal_title:International journal of computer assisted radiology and surgery
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journal_title:International journal of computer assisted radiology and surgery
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更新日期:2015-05-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
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更新日期:2014-03-01 00:00:00
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更新日期:2020-12-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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更新日期:2016-08-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
doi:10.1007/s11548-015-1347-2
更新日期:2016-08-01 00:00:00
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更新日期:2015-06-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
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更新日期:2019-03-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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更新日期:2014-09-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
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更新日期:2014-07-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
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更新日期:2018-03-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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journal_title:International journal of computer assisted radiology and surgery
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pub_type: 杂志文章,评审
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更新日期:2016-09-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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更新日期:2009-05-01 00:00:00
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journal_title:International journal of computer assisted radiology and surgery
pub_type: 杂志文章
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更新日期:2016-12-01 00:00:00